The overall goal of this proposal is to develop a single-cell, and network-level understanding of cell signaling mechanisms involved in adaptive drug responses through the application of engineering and systems biology approaches. I have chosen melanoma and drugs targeting the BRAFV600E oncoprotein, since adaptation is well known to be important in this type of cancer. Treatment of BRAFV600E melanomas with drugs, such as vemurafenib, that inhibit RAF/MEK signaling is effective in the short term, but remission is not durable. Drug resistance is thought to involve short-term adaptive responses that up-regulate compensatory pro-growth and/or anti-apoptotic mechanisms. The discovery and analysis of adaptive responses in melanoma represents a breakthrough in tumor biology and reveals hitherto unsuspected plasticity in signaling biochemistry. However, systematic data comparing BRAFV600E tumor cells is generally lacking and important questions are unanswered. It is not known whether adaptive mechanisms in different cell types are fundamentally similar or they are different from one cell type to the next or even one single cell to the next. Further, it is not clear how different adaptive responses are related to each other, how they are affected by tumor microenvironment, and how they are integrated to determine the fate of an individual cell. Answering these questions is critical for developing single or multi-component biomarkers of drug responsiveness and for designing rational and effective combination therapies to overcome drug adaptation and ultimately drug resistance. Our previous studies show that adaptive responses are diverse across melanomas, involving different combinations of signaling cascades. In particular, we identified an adaptive mechanism involving JNK/c-Jun that diminishes drug efficacy. RAF and JNK inhibitors induce synergistic cell killing in melanoma cells in which c-Jun mediated adaptive response occurs. Single-cell studies show that JNK inhibition enhances suppression of phospho-S6 ribosomal protein, promotes apoptosis in a subset of cells that would otherwise become quiescent and apoptosis-resistant in the presence of vemurafenib alone, and increases drug maximal effect (Emax). This work identified involvement of different pathways in adaptive responses, their diversity with genotype and time, and suggested that it would be critical to examine the diverse phenotypes induced by BRAFV600E inhibition at a single-cell level. Therefore, in this proposal I will couple high-throughput measurement, fixed and live single- cell analysis, and a combination of statistical and mechanistic computational modeling techniques to: (1) identify key molecules (ligands, receptors and transcription factors) linked to JNK/c-Jun mediated adaptive response and crosstalk with other adaptive responses in a set of BRAFV600E melanoma cell lines and primary patient-derived melanoma cells having different genotypes, (2) develop network-level models of adaptive response which discriminate among key adaptive network states observed across different cell types and their association with phenotypic responses and drug sensitivity, (3) assess the diversity and magnitude of adaptive responses across individual cells and determine their association with individual cell phenotypes (proliferation, quiescence, senescence, cell death, etc.), (4) investigate the contribution of other cell types within the tumo microenvironment, in particular tumor-associated macrophages, in drug-induced adaptive and phenotypic responses, and (5) utilize these data to identify mechanism-based biomarkers for different pathway adaptations, use these biomarkers to design and test novel combination therapeutics that take into account malignant cells, the tumor microenvironment, and the dynamics exerted by the treatment itself. The success of these studies is directly linked to the proposed training activities I intend to undertake during the mentored phase of this award. I believe that with my extensive engineering and computational background, being awarded a K99/R00 award will allow me to deepen my understanding of tumor biology (concentrating initially on melanoma) and to obtain advanced training in a highly supportive and innovative training environment of Harvard Medical School. In addition, to support me in my training, and in my transition to the independent phase of my career, I will be benefitting from the mentorship and collaboration with leading experts in the fields I propose studying. This includes my mentor Dr. Peter Sorger (Harvard Medical School), and collaborators Dr. Neal Rosen (Memorial Sloan Kettering Cancer Center), Dr. Nathanael Gray (Dana Farber Cancer Institute), and Dr. Steve Gygi (Harvard Medical School). The skills and knowledge acquired during the mentored phase of this award will be instrumental for the above proposed studies and future studies, and for successfully launching my career as an independent investigator.
Drug adaptation in BRAFV600E melanomas limits therapeutic effectiveness and appears to promote the emergence of cells carrying resistance mutations, the primary challenge facing targeted anti-cancer drugs. My work will combine measurement and computational modeling to characterize adaptive responses in a systematic manner, determine the impact of tumor microenvironment on adaptation and analyze the effectiveness of various combination therapies, thereby laying the foundation for a rational approach to improving the durability of therapeutic response.
|Fallahi-Sichani, Mohammad; Becker, Verena; Izar, Benjamin et al. (2017) Adaptive resistance of melanoma cells to RAF inhibition via reversible induction of a slowly dividing de-differentiated state. Mol Syst Biol 13:905|
|Lin, Jia-Ren; Fallahi-Sichani, Mohammad; Chen, Jia-Yun et al. (2016) Cyclic Immunofluorescence (CycIF), A Highly Multiplexed Method for Single-cell Imaging. Curr Protoc Chem Biol 8:251-264|
|Tirosh, Itay; Izar, Benjamin; Prakadan, Sanjay M et al. (2016) Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 352:189-96|